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Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 9 months ago
Here is the exercise.
And here is the spreadsheet you’ll need for the exercise [In-Class Exercise 12.2 – Sentiment Analysis Tools.xlsx].
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Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 9 months ago
Here is the exercise.
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Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 10 months ago
Here is the assignment. Due Dec 4.
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Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 10 months ago
Here is the exercise.
Here is the excel spreadsheet you will need to complete this exercise [In-Class Exercise 11.2 – NCAA 2013-2014 Player Stats]
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Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 10 months ago
Here is the exercise.
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Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 10 months ago
Leave your response as a comment on this post by the beginning of class on November 15,. Remember, it only needs to be three or four sentences. For these weekly questions, I’m mainly interested in your opinions, n […]
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One of the biggest issues we faced was deciphering all of the data. There was a huge amount of data which contained multiple errors and it was very difficult to pick my way through. Once the data was deciphered it went off without a hitch, but this initial challenge was very tough to overcome.
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If I were to try and access the data from Blackboard, the columns would represent course, grades, assignments, and announcements. The columns would then have the name of the course, the grade in it, assignments, and the announcements as well as the names of the instructors/professors.
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I would use Amazon.com where the columns would be the departments, deals, browsing history, sign in, orders, cart. In each column starting with departments, includes all the categories where you can choose to buy something, the deals would have all the types of deals, the browsing history will show you what you have searched up, the sign in would show you a text box to enter username and password, the orders will show you orders, and the cart will show you what you have added to your cart.
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I’m in charge of emailing list for Temple Consulting Club. I keep track of attendance as well as active membership of students. Th columns are: Student Name, TUID, TUEmail, Graduated Year, Major. The rows are the data insert of attendees and upcoming active members of the club.
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I usually use WebAssign, the site that allows professors to assign the homework online. The score of the homework will be graded by computer, so I can see my score after I finish the assignments. I can rerecord my list of the score by creating each row for each assignment and columns for the number of homework, score, and date.
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I would want to store data in a spreadsheet for Canvas because the site informs me of upcoming assignments, current grade, and any announcement for class. The row would be the courses that I am currently taking. Some of the columns would be number of announcements, number of assignments, current grade, number of people in class, and number of files.
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A data-driven service that i often use is Canvas. If i wanted to store data for them in a spreadsheet, The column would be the courses, time, location and the name of the professor. The rows would be the attendance, assignments, tests, exams, and homework with the due dates.
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One data-driven source that I use a lot is Twitter. The columns would represent different twitter accounts/profiles and then the rows would be the different things that account has liked or retweeted. The rows could also represent the amount of likes a retweets that each individual post received. Columns could also represent different subjects of posts such as animals, politics, sports, etc instead of by profile.
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I choose Blackboard to store data for the information of the course, grade, location etc. The data I would like to place in the column section are grade, credit hour, time of the class, class location, instructor’s name, homework, and coming test date. For the row section, I will put in class name with its abbreviation and related semester. By placing data this way, student can have a clear look for their class, especially “homework” and “coming test date” can remind and let student be aware of their schedules. The “grade” column can provide student a measure of their performance.
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If I were using Blackboard data in Excel, the columns would be the class, and the rows would be my quiz, test, homework, and project averages for that class. This would help me keep track of all my grades at a glance.
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I would use Canvas where the columns will have the name of the course and professor, assignments that due or any future ones, grades from the homework, quizzes, and exams. This would be a representation of expectations of the course, and on my behalf what it takes to get an A.
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One data driven service I use is Amazon. A row would be the product I have ordered. The columns would be the cost of the order, the date it was ordered, the date it was shipped, the date it was received, and a review of the product.
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If I were using blackboard, some of rows would be grades, assignments, discussions, etc. The data columns would be the data pertaining to each row. This could include assignment names, assignment grades, assignment due dates, etc.
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I data-driven I use is Twitter, I would add users accounts in columns and in rows I would add a row for each: number of following, number of followers, number of tweets, number of tweets and replies, media, and likes.
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Amazon has a huge database, I use Amazon a lot. Every time I log in Amazon, the rows would be my account, orders, prime and shopping cart. The columns would be many types conditions or filters for the things I searched, like the price interval, the color, the brand and so on.
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I am willing to choose Canvas to store data about information of my academic study plan. In the row section, I would like to put the courses’ name and number. The data I would like to put in the column section are class’s time, location, professor’s information, and upcoming events such as homework and exams’ due date. Also, I prefer putting the semester’s information, like which semester I took this, and how many credit hours I earned from this course.
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I use blackboard everyday to check homework and my grades. For the rows, it would be grades, assignments and announcements whereas the columns would be the grade received for certain assignments, name of the assignments, and the specific date that the announcements have been made.
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I think that the rows would be user names or profile names. This would help since it should be user by user data not platform based. Each user would have data recorded in the columns about time on the platform, time of login, type of user, some measurement of activity, and maybe other credentials of the user depending on security.
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I wanted to make sure I said that blackboard and tuportal were my choice data sights.
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I use blackboard almost everyday.
I would make the columns Grade, location, professor, credit hours worth. and then I would make the rows the names of classes. I could use this to track all the classes that I have taken and will take at Temple. Any other user could fill in his or her information as this is a very universal tool. -
I often use blackboard, and for a spreadsheet for blackboard the rows would represent the classes that i take. The columns would be my grades on tests, assignments, homework, and it would count attendance.
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I check my grades from blackboard everyday. If I were to create a spreadsheet for my personal grades to keep track, some columns would be attendance, homework, projects, quizzes, test, and overall score. Rows would consist of class title and professor name. I would insert the data into each field by putting in my grade for each specific column and taking the average for an estimated overall grade that I have so far in the semester.
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I use a Node Module called System information nearly everyday to map out the status of my server. It has many sheets available, but let’s take one example, si.cpu():
it has these columns:
manufacturer e.g. ‘Intel(R)’
brand e.g. ‘Core(TM)2 Duo’
speed in GHz e.g. ‘3.40’
speedmin in GHz e.g. ‘0.80’
speedmax in GHz e.g. ‘3.90’
cores # cores
vendor Vendow ID
family Processor Family
Model Processor Model
stepping Processor Stepping
revision Revision
cache cache in bytes (object)
cache.l1d L1D (data) size
cache.l1i L1I (instruction) size
cache.l2 L2 size
cache.l3 L3 sizeI use this data to map out every detail about the server.
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Amazon is a data-driven service I use frequently, the columns could be ordered day, price, quantity, color, size, delivered day, name of vender. And the row could be the name of the product.
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I use the ESPN Fantasy Football a lot during the NFL season and the app is full of data. Rows in the spreadsheet would contain different data, such as player name, player position, fantasy points scored, projected fantasy score, etc.
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If I were to attempt to organize my tweets I would create a spread sheet featuring Columns like Date, #Likes, #Retweets, tweet contents (text, .img, .mp3, video) and the tweet itself. This would allow me to better understand the performance of my tweets.
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If I were to attempt to organize my tweets I would create a spread sheet featuring Columns like Date, #Likes, #Retweets, tweet contents (text, .img, .mp3, video) and the tweet itself. This would allow me to better understand the performance of my tweets. the row would represent the overall performance.
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i have used canvas a lot since i started to study in college and the app provide me full data of courses. the row contain multiple of data such as name course, course number and the season of the course whereas the columns provide announcement, assignments, and grades and more. this would let me know better on how my course processing and if i doing well on the course. the row will let me know what course do i register for the semester or quarter.
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If I was storing data from twitter in an excel sheet I would use each account as the row. And in columns I would have their first and last name, number of tweets, number of likes and retweets, number of followers, number of people they follow, when the account was activated, and any links they may have to other social media accounts or websites.
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For Amazon, there will be users/order/product/address rows. And columns as following:
Users: user_id, age, address_id, order_id
Order: order_id, user_id, product_id
Product: prodcut_id, description
Address: address_id, state, city, zip_code -
I work for Amazon so that’s easy for me. For columns I would put item number, name, description, if it’s prime or not, price, shipping, ratings.
However, I would separate the rows by categories and departments. -
This is Seth Dennis. I never signed in and the name is autofilled.
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On Amazon.com I tend to purchase many blu-rays. The rows for these purchases would be the name of the movies I purchased. The columns would include the price, year of release, rotten tomatoes score, type of blu-ray and genre of the movie. This is exactly what the data would look like if I were to implement it onto a spreadsheet.
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I would use Facebook. I would use their profile account in the column and I would add a few other rows for Facebook. I would use the numbers of friends they have. They number of people who want to become their friends. How many post they have. Also, how many pictures they post. Lastly how many statuses they like.
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I would use Canvas to store data. Canvas will remain me the coming up assignments which i should finish them. In addition, i can see my grade on it and we can see how many tasks we finished recently. In some rows, it will show how many courses you are taking, and you can see the courses’ name and the professor’s name of them.
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In blackboard, the rows could be the class names while the columns include overall grade, attendance, test average, quiz average, and homework grade.
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Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 10 months ago
Some quick instructions:
You must complete the quiz by the start of class on November 13
When you click on the link, you may see a Google sign in screen. Use your AccessNet ID and password to sign in. […] -
Nhi Nguyen and
Sezgin Ayabakan are now friends 6 years, 10 months ago
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Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 10 months ago
Here are the assignment instructions. The assignment is due December 4. We’ll do the presentations on Monday and Wednesday.
This is a GROUP project so you may not do this assignment on your own or in sma […]
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Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 10 months ago
Prince has just got a confirmation on the room. He will be holding an exam review session tomorrow, Thursday (Nov 2) at 6:30pm in Alter Hall Room 748.
===> LINK TO THE VIDEO CAPTURE
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Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 10 months ago
Leave your response as a comment on this post by the beginning of class on November 8. Remember, it only needs to be three or four sentences. For these weekly questions, I’m mainly interested in your o […]
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The biggest challenge for me is when I tried to visualize my assumption from my data analysis. At first, I found it was hard for my to transfer numbers to pictures, and to make the data easier for the public to perceive. I have to acknowledge that the readers are mainly average people, who might not encounter Tableau or any data analysis tools. Therefore, I used common indicator and easy charts to illustrate my points. I also used related objects of the theme to draw more attention and engage people to read my infographic.
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The biggest challenge in assignment 4 was the format of the data in excel file. I spent a lot of time to clean the data before creating the visualizations. The example of the format problem is that the date was in the format that I cannot use to create the visualization. Then I need to change them into the right format, which was a very time-consuming process.
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The biggest challenge for me was trying to figure out what infographics we had to choose for our visualization. We all tried to go online to various websites to find which infographic would be correct for what we were trying to solve. We decided to create our own infographics by drawing on the paint tool online. We then eventually found out which one we would use for the assignment. It helped a lot that everyone in our group was finding the right one and drawing it out. Eventually, we were resolved it.
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The biggest challenge in assignment 4 was cleaning data. Many movies are classify into 3 or more genre, it is hard to create visualization I have to classify the genre of the movie and clean usefulness and wrong data. This process cost a lot of time because of the huge amount of data.
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The biggest challenge in assignment 4 was cleaning the data. Because the movie excel spreadsheet consisted of so much data, there are clearly things to clean up. In order to understand the data in a better way, we had to narrow it down to specifics as well as filtering. This was challenging because cleaning data takes time and effort and it can also become frustrating at times.
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One of the biggest challenge in assignment 4 was trying to figure out how to start because there were no specific direction or layout of what we should do. All of the in class assignment had a set of directions but for this assignment it was more open. When we all met up to start the assignment the first time, I was confused on what to put in tableau for creating the graph.
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the biggest challenge in assignment 4 for me is to find weather, times and history event information for the question requirements. At first we were really confusing on how to find the specific information on each requirement called. After that we finally find a way to come up with combining weather and history event together on a website and used it for the assignment.
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the biggest challenge that was faced was cleaning the data. Each member of the team was assigned a movie category. my category was Horror. i had difficulties cleaning the data because it was so much…categories within categories ( horror and its sub-categories, such as drama, comedy, parody, action ,adventure and much more) i was eventually able to clean it through filter in excel and be productive in my group work.
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The biggest challenge for me in assignment 4 was cleaning the data on the excel file. I could clean one set of data without messing up another data. I would try to just use data for Drama movies but it would do it for all the movie genres. I found it to be easier to clean the data set on Tableu it self.
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The biggest challenge for me during assignment 4 was trying create data visualizations in tableau. There were certain visualizations that were easy to construct and supported the points we were trying to make, but as the data got more advance, the construction of visualizations and charts became much more difficult. Also, it was very difficult to construct concise visualizations that directly related to the questions we were trying to answer.
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The biggest challenge for me during the assignment 4 is to analyze the data professionally and accurately. The challenge my team chose was from Comcast. When dealing with the giant dataset, Excel and Tableau skills are significantly necessary. However, as a newer and a learner of Tableau, I made mistakes and errors during the process. Therefore, it took us a great deal of time to correct possible errors and check the reliability of our analysis. Another challenge is to meet periodically with the team members, the different majors and different schedules we had affect the performance of our infographics.
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The biggest challenge for me in Assignment #4 is Piktochart is a software which take time to get used to, because the function is limited and not fully convenient. The way we solved this problem was I asked my friend who is more familiar than us on using this technique in order to help us take advantage on Piktochart as much as possible. Also, it was challenged to get every team member agree on a fragment of the design due to different members have various perspectives. Fortunately, one of our member major in Arts & Music who usually has better design thinking and is capable to make a final decision. Furthermore, it was not easy to meet with other team members frequently due to we all in different majors and have different schedules. If we really could not have a group meeting, we just worked separately and tried our best to finish our own work firstly and then met with each other. Therefore, we could combine our work together without changing that much.
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the biggest challenge in assignment 4 for me was how to use the data given to answer the questions. in other words, how can I answer the questions by visualizing the data I have. Coming up with the right answers to the questions was the longest part for me. for example, how to use the Pfizer data to answer their questions about the effect of smoking on society.
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The biggest challenge my group encountered while working on Assignment 4 was creating the visualization portion of the project. Creating the graphs also posed a challenge however once we figured out what data sets we wanted to use, the graphs were made. Once we started crafting the infographic it was challenging making the graphs look pleasing. We had to brain storm and decided photoshop was the best option. Once this was done the whole infographic looked better.
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The biggest challenge for me is making sure a fundamental direction to analyze data. Too many data over there, we spend huge time to choose some data that we think it is useful. And we also try many ways to analyze. But picking up a way that four of us all agree is very difficult. We wast huge time on finding suitable analyze way.
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The biggest challenge of assignment 4 is to select the useful data. I screened out the bad data and selected the data that could be useful to the problem we tried to solve. And turned the data that I chose to information, and analyzed the information we got. Then we set a threshold to narrow the range of information that should be analyzed.
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The biggest challenge in the assignment 4 for me is to analyze the data correctly and briefly. It’s would be a totally different result if I can’t tell the information from data in a right way, the audiences would think in a wrong way about the data, then they would never get the true information they want. It’s very important to lead people to really understand the information that comes from the data.
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It sounds kind of silly, but our groups biggest challenge was trying to figure out what exactly the professor was looking for considering this assignment didn’t come with a straight guideline. This was more of an open ended assignment which allowed the class to have freedom in how their assignment was constructed, which can be fun, however, it can also make the project a little more stressful because you don’t know if you’re giving the professor what they’re looking for or if you are not doing something right. So I think that was the biggest challenge for our group.
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One of the biggest challenges for me was deciphering which data to use and how to use it. Since a lot of data was missing it was important for me to try and keep the analysis as unbiased as possible with the numbers we were given to ensure a good read on our information.
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The biggest problem in assignment 4 was trying to navigate through the data and determining what need to be used and when, along with if certain parts of the given data needed to be cleaned. To resolve this problem we experimented with many different ideas, something like trial and error until we came up with what we found to be the best way to go about it.
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The biggest challenge for me on assignment 4 was figuring out what to do with the data given. It was tough to decide what we wanted to create on a graph with the data given. We resolved this problem by thoroughly looking through and cleaning the data to determine how we wanted to show our charts.
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The biggest challenge of assignment 4 is to choose the right date to analyze it. Since we have too much data in the website, we cannot choose the best one in a very short time. In addition, there are a lot of wrong data that we cannot use in a directly way, so we should delete those data that will affect our results.
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The most prominent challenge was trying to find the best approach for counterarguments. As a team, we did eCommerce and us to think outside of the box and understand why people would form their arguments, to begin it. Instead of trying to find the best answer, we directly gathered as much data supporting our thesis and conclusion. For instance, one may argue that people in affluent zip codes order stuff more than not so fortunate people. A counter-argument could be that it’s just coincidental and those people in the less affluent could just be wealthy and bit order as much. Or even is close to a shopping mall and have resources in their reach, so they do not have to rely on the internet. There are lots of ways to go by this, and as a team, we combated these type of issues.
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The biggest challenge our group faced during assignment 4 was coming up with good graphics. To fix the problem we first eliminated outliers from the graphs by excluding them. Next we created a calculated field to further how good the graph was at displaying our desired information.
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The biggest challenge for me was how to use the given data to answer the questions and then use the tableau to create the visualization.
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The hardest part of Assignment 4 was figuring out a general plan when starting out. Going through all of the available data and determining which sets were most important proved to be difficult. This especially made it difficult to figure out a plan for how we wanted to present the information later on.
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The biggest challenge was knowing specifically what to use and cleaning up the data. It was very time consuming and honestly, it should’ve been the only assignment for the class, at least the first half. All the lessons we learned could’ve been applied to this one assignment and it would’ve definitely helped us understand it more. The issue as to why I didn’t really know what to do is because the in-class assignments tell us exactly what to do instead of actually learning what we’re doing.
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The biggest challenge in assignment 4 was figuring out how to make our graphics clear. Tableau is a software that we’re all still trying to get the hang of so it wasn’t easy to translate the questions into graphics. Eventually we came together and figured out a way to make our graphics represent the questions we were answering. It was all about team work by the end of the project.
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For me and my group we found that the hardest part of assignment four was creating an infographic. We struggled to use the website Piktochart that we had worked on previously in class during one of the in-class exercises. We found it hard to make graphs and other graphics on the site itself and and had to end up importing graphs from Tableau that stuck out visually and did not fit the color schemes or themes of the rest of the info graphics.
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The biggest challenge is to use the Piktochart design. Because it takes a lot of time to look for the proper background and section to correspond our team topic. Also, I need to select the best color for the background.
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One of the biggest issues we faced was deciphering all of the data. There was a huge amount of data which contained multiple errors and it was very difficult to pick my way through. Once the data was deciphered it went off without a hitch, but this initial challenge was very tough to overcome.
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One of the biggest issues we had was just trying to figure out what to do. When we did figure out what to do, getting the right kind of chart was difficult. We eventually figured it out and it turned out to be not that hard. As a group we thought we had to make a poster on piktograph. When we found out that we didnt need that either, the assignment was okay.
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The biggest challenge in assignment 4 is cleaning data.Because there are lots of dirty data in the database, I had to spend much time to clean the dirty data or uncompleted data. I use filtrate and sort button to find the dirty data and clean the data.
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Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 10 months ago
Some quick instructions:
You must complete the quiz by the start of class on November 6
When you click on the link, you may see a Google sign in screen. Use your AccessNet ID and password to sign in. […] -
Sezgin Ayabakan's profile was updated 6 years, 10 months ago
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Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 10 months ago
Upcoming Monday (Oct 30), we will have a guest speaker from Comcast Headquarters in Philadelphia: Randy Zwitch. His bio is below:
Randy Zwitch is Principal Data Scientist at Comcast Headquarters in Philadelphia. […] -
Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 10 months ago
Here is the study guide for the first exam.
Couple of items for your attention:
Exam #2 is on Nov 3, Friday at 4pm.
One of our MIS PhD Students will proctor the exam. I will be at a conference.
If […] -
Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 10 months ago
Here is the exercise.
And here is the Excel workbook you’ll need [Pew Story Data (Jan – May 2012).xlsx]
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Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 10 months ago
Here is the exercise.
And here are the workbooks [2012 Presidential Election Results by District.xlsx and Portrait 113th Congress.xlsx]
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Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 10 months ago
Here is the exercise.
And here is the spreadsheet to complete the exercise [In-Class Exercise 8.2 – OnTime Airline Stats [Jan 2014].xlsx].
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Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 10 months ago
Here is the exercise.
Comment under this thread. One comment from each team. One KPI and how it relates to the SMART criteria.
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Fours’s Company: Time logged on project.
It is specific and measurable as you can see the time worked on a document and it is quantifiable. It is also reliant to the project as the time put in should be equal to effort given. You can also track it over a period of time. -
Team name: Datanova
KPI: “The length of time each member spend to support team project for each week.”
Specific: Each memeber spend their individual time to support team project each week.
Mearsureable: The length of time.
Achieveable: Each person spend time on team project.
Revelent: The longer team each memeber contribute, the better may the result comes.
Time based: “Each week” is time based and can be measured with “days” and “week.” -
The KPI for our group C.A.S is: “Number of tasks finished per day by each group member” It is specific and measurable by the number of tasks, achievable so each group member will only do number of tasks from the whole project, relevant to the project and finally time phased per day.
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Ryan Northey and Will Bolendz
KPI: Number of times gone to group meetings
Specific: Detailed and easy to measure
Measurable: Easy just to count how many times a student goes to the group meetings
Achievable: You can achieve this data by counting the number of times a student attends the group meetings
Relevant: Helps see how engaged the student is in the project
Time phased: Number of times gone to group meetings is a measurement over time -
Communication- Students communicate punctually within 24 hours of initial contact.
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-How much time did they put into the project
-How much work did they do -
TBD (Phil, Melissa, Matt, Shayna, Christia): number of group meetings missed/attended
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Sezgin Ayabakan wrote a new post on the site MIS 0855: Data Science Fall 2017 6 years, 10 months ago
Some quick instructions:
You must complete the quiz by the start of class on October 23
When you click on the link, you may see a Google sign in screen. Use your AccessNet ID and password to sign in. […] - Load More